resume-analysis

Resume interrupted analysis pipelines from the latest READY agents.

21|11|Updated Mar 15, 2026
One-click install
npx skills add https://github.com/ai-analyst-lab/ai-analyst-plugin --skill resume-analysis
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: resume-analysis
Source: https://github.com/ai-analyst-lab/ai-analyst-plugin/tree/main/skills/resume-analysis
Command: npx skills add https://github.com/ai-analyst-lab/ai-analyst-plugin --skill resume-analysis

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Resume an interrupted analysis pipeline by reading pipeline state and continuing from the next READY agents.

Core Features & Use Cases

  • State-aware resume: detects paused/failed runs and restarts only the pending steps with complete dependencies.
  • Per-run and legacy support: handles per-run directories, V1-to-V2 migrations, and artifact-based fallbacks.
  • DAG-driven orchestration: reconstructs a READY plan from the registry and re-triggers execution through the DAG walker.

Quick Start

Say '/resume-analysis' to resume the most recent analysis from where it left off.

Frequently Asked Questions about resume-analysis

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I resume an interrupted data analysis pipeline from where it failed?▼

To resume an interrupted data analysis pipeline, the system reads the latest pipeline state and continues execution from the next READY agents. It reconstructs a dependency-aware plan using the DAG registry, ensuring only pending steps with complete dependencies are restarted.

What happens to paused or failed steps when I restart an analysis pipeline?▼

When restarting an analysis pipeline, state-aware resume detects paused or failed runs and restarts only the pending steps. It uses artifact-based fallbacks to construct a consistent resume plan and re-triggers execution through the DAG walker.

How does DAG orchestration handle dependency-aware readiness for pending agents?▼

DAG orchestration handles dependency-aware readiness by reading the registry.yaml and current agent outputs. It identifies which agents are READY based on completed dependencies, ensuring the workflow resumes consistently without re-running successful steps.

Can I migrate from a legacy V1 pipeline state to V2 when resuming a data analysis run?▼

Yes, you can migrate from a legacy V1 pipeline state to V2 when resuming a data analysis run. The workflow handles per-run directories and optional V1-to-V2 migration, allowing you to continue legacy workflows on the updated DAG walker architecture.

Do I need specific directory structures to resume an interrupted analysis workflow?▼

You need per-run directory structures to resume an interrupted analysis workflow. The system reads registry.yaml, current state, and agent outputs from these directories to construct a consistent resume plan, while also supporting legacy per-run layouts through artifact-based fallback.